Applications of Artificial Neural Network Technique To Polypyrrole Gas Sensor Data for Environmental Analysis

Abstract

In this study, the electrochemical deposition technique was used to fabricate Polyprrole thin film. The QCM piezoelectric sensors have been used to investigate the possible sensing mechanisms and adsorption-desorption kinetics of the polyprrole films to compare sensor sensitivities of the atmosferic gasses such as humidity, CO2 and O2. The Langmuir model and ANN Technique have been used to Polypyrrole Gas Sensor Data for environmental analysis. For this, feedback, three layer ANN has been used for the experimental data for adsorption and desorption process of PPY versus humidity, PPY versus CO2 and PPy versus O2. Different number of hidden layer used in this work and good result gets with 14 neurons. Totally 2064 experimental data used for fitting ANN. The randomly selected data was used to training and the ANN was terminated when the error was less than 10-3.